generate_heatmap.R

df <- read.table(file="data.txt", sep="\t", stringsAsFactors = F, header=T)
maxes <- apply(df[, c(-1)], MARGIN=1, FUN=max)
#find maximum values per row
#the negative index corresponds to column 1, containing the gene identifiers
normdf <- sweep(df[, c(-1)], MARGIN=1, FUN="/", maxes)
#divide all the values by the corresponding maximal value
dfn <- data.frame(Gene=df$Gene, normdf)

library(reshape2)
dfn.m <- melt(dfn)

mybreaks <- c(-0.1, 0.25, 0.5, 0.75, 1.1)
mylabels <- c("0-25%", "25-50%", "50-75%", "75-100%")
numbertocategory<- function(vctr, brks, lbls){
  return(cut(as.numeric(vctr), brks, lbls))
}
numbertocategory(dfn[1, -1], mybreaks, mylabels)
# [1] 50-75%  50-75%  50-75%  75-100% 75-100% 75-100%
#   Levels: 0-25% 25-50% 50-75% 75-100%

categ <- apply(dfn[, -1], MARGIN=2, numbertocategory, mybreaks, mylabels)

mydf <- data.frame(Gene=dfn$Gene, categ)
#       Gene   Cell1   Cell2   Cell3   Cell4   Cell5   Cell6
#   1   Gene1  50-75%  50-75%  50-75% 75-100% 75-100% 75-100%
#   2   Gene2  25-50%  25-50%  25-50% 75-100% 75-100%  50-75%
#   3   Gene3  25-50%  25-50%  50-75%  50-75%  25-50% 75-100%
#   4   Gene4   0-25%   0-25%  25-50%  50-75% 75-100% 75-100% etc...

nms <- names(mydf)
lnms <- length(nms)
rowsall <- length(mydf$Gene)
colsall<- length(names(mydf[, c(2:lnms)]))
rowIndex = rep(1:rowsall, times=colsall)
#1  2  3  4  5  6  7  8  9 10 11 12
#1  2  3  4  5  6  7  8  9 10 11 12 etc...
colIndex = rep(1:colsall, each=rowsall)
#1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 3
#3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 5 5...etc
mydf.m <- cbind(rowIndex, colIndex ,melt(mydf, id=c("Gene")))
#     rowIndex colIndex Gene   variable value
# 1         1        1  Gene1    Cell1  50-75%
# 2         2        1  Gene2    Cell1  25-50%
# 3         3        1  Gene3    Cell1  25-50%
# 4         4        1  Gene4    Cell1   0-25%
# 5         5        1  Gene5    Cell1 75-100%
# 6         6        1  Gene6    Cell1 75-100%

#NOW, the plotting:
p <- ggplot(mydf.m, aes(variable, Gene))+
  geom_rect(aes(x=NULL, y=NULL, xmin=colIndex-1,
                      xmax=colIndex,ymin=rowIndex-1,
                      ymax=rowIndex, fill=value), colour="grey")
p <- p+scale_x_continuous(breaks=(1:colsall)-0.5, labels=colnames(mydf[, c(-1)]))
p <- p+scale_y_continuous(breaks=(1:rowsall)-0.5, labels=mydf[, 1])
p <- p+theme_bw(base_size=8, base_family = "Helvetica")+
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    panel.border = element_blank(),
    axis.ticks.length = unit(0, "cm"),
    axis.text.x = element_text(vjust=0, angle=90, size=8)
  )+ 
  scale_fill_manual(values = c("white","yellow","orange", "red"))
p